THE FORMATION OF HABITS The implicit supervision of the basal ganglia

Size: px
Start display at page:

Download "THE FORMATION OF HABITS The implicit supervision of the basal ganglia"

Transcription

1 THE FORMATION OF HABITS The implicit supervision of the basal ganglia MEROPI TOPALIDOU 12e Colloque de Société des Neurosciences Montpellier May 1922, 2015

2 THE FORMATION OF HABITS The implicit supervision of the basal ganglia MEROPI TOPALIDOU 12e Colloque de Société des Neurosciences Montpellier May 1922, 2015

3 THE FORMATION OF HABITS The implicit supervision of the basal ganglia MEROPI TOPALIDOU 12e Colloque de Société des Neurosciences Montpellier May 1922, 2015

4 GoalDirected Actions VS Habits Belin et al. (2008), Yin (2008), Foerde & Shohamy (2011), Doll et al. (2012)

5 GoalDirected Actions VS Habits initiation of response is under direct control of the current value of outcome Belin et al. (2008), Yin (2008), Foerde & Shohamy (2011), Doll et al. (2012)

6 GoalDirected Actions VS Habits initiation of response is under direct control of the current value of outcome Belin et al. (2008), Yin (2008), Foerde & Shohamy (2011), Doll et al. (2012)

7 GoalDirected Actions VS Habits initiation of response is under direct control of the current value of outcome sensitive to devaluation of the outcome Belin et al. (2008), Yin (2008), Foerde & Shohamy (2011), Doll et al. (2012)

8 GoalDirected Actions VS Habits initiation of response is under direct control of the current value of outcome direct initiation of responding by stimulus and/or context presentation sensitive to devaluation of the outcome Belin et al. (2008), Yin (2008), Foerde & Shohamy (2011), Doll et al. (2012)

9 GoalDirected Actions VS Habits initiation of response is under direct control of the current value of outcome direct initiation of responding by stimulus and/or context presentation sensitive to devaluation of the outcome Belin et al. (2008), Yin (2008), Foerde & Shohamy (2011), Doll et al. (2012)

10 GoalDirected Actions VS Habits initiation of response is under direct control of the current value of outcome sensitive to devaluation of the outcome direct initiation of responding by stimulus and/or context presentation resistant to devaluation of the outcome Belin et al. (2008), Yin (2008), Foerde & Shohamy (2011), Doll et al. (2012)

11 GoalDirected Actions VS Habits initiation of response is under direct control of the current value of outcome sensitive to devaluation of the outcome direct initiation of responding by stimulus and/or context presentation resistant to devaluation of the outcome behavior adjusts to reflect the new value of the outcome that the action would obtain Belin et al. (2008), Yin (2008), Foerde & Shohamy (2011), Doll et al. (2012)

12 GoalDirected Actions VS Habits initiation of response is under direct control of the current value of outcome sensitive to devaluation of the outcome direct initiation of responding by stimulus and/or context presentation resistant to devaluation of the outcome behavior adjusts to reflect the new value of the outcome that the action would obtain habits persist even if the reward becomes less attractive or if the action is not necessary to earn the reward. Belin et al. (2008), Yin (2008), Foerde & Shohamy (2011), Doll et al. (2012)

13 Cortex Basal Ganglia Novel behaviors require attention and flexible thinking and therefore are dependent on cortex, whereas automatic behaviors has been assumed to be primarily mediated by subcortical structures. Much evidence suggests however, that subcortical structures, such as the striatum, make significant contributions to initial learning. More recently, evidence has been accumulating that neurons in the associative striatum are selectively activated during early learning, whereas those in the sensori striatum are more active after automaticity has developed. At the same time, other recent reports suggest that automatic behaviors are striatum and dopamineindependent, and may be mediated entirely within cortex. Resolving this apparent conflict should be a major goal of future research. These ideas led to the theory that dominated the 20th century: Novel behaviors require attention and flexible thinking and therefore are dependent on cortex, whereas automatic behaviors require neither of these and so are not mediated primarily by cortex. Instead, it has long been assumed that automatic behaviors are primarily mediated by subcortical structures.

14 Cortex Basal Ganglia Goal Directed actions go here Cortex leads decision once learned Habits go there BG teach cortex during learning phase Daw, Niv & Dayan (2005) Ashby, Turner & Horvitz (2010) Novel behaviors require attention and flexible thinking and therefore are dependent on cortex, whereas automatic behaviors has been assumed to be primarily mediated by subcortical structures. Much evidence suggests however, that subcortical structures, such as the striatum, make significant contributions to initial learning. More recently, evidence has been accumulating that neurons in the associative striatum are selectively activated during early learning, whereas those in the sensori striatum are more active after automaticity has developed. At the same time, other recent reports suggest that automatic behaviors are striatum and dopamineindependent, and may be mediated entirely within cortex. Resolving this apparent conflict should be a major goal of future research. These ideas led to the theory that dominated the 20th century: Novel behaviors require attention and flexible thinking and therefore are dependent on cortex, whereas automatic behaviors require neither of these and so are not mediated primarily by cortex. Instead, it has long been assumed that automatic behaviors are primarily mediated by subcortical structures.

15 Outline Experiment Computational model Results

16 Experimental setup Two monkeys, simple twoarmed bandit task with P=0.75 and P=0.25. Habitual condition (known stimuli pair, same every day) Novel condition (unfamiliar stimuli pair, new every day) Habitual Condition Trial start Cue presentation Go signal Decision Reward Trial stop Prelearned cues Novel Condition Novel cues (every day) s 1.5s 1.0s 1.5s 1.0s 1.5s Time Piron et al. (submitted)

17 Experimental results 1.0 Mean success rate saline HC Number of trials NC Mean success rate * HC NC Saline Mean of first 25 trials * HC NC Saline Mean of last 25 trials Piron et al. (submitted)

18 Experimental results Muscimol injection in GPi disrupts learning in novel conditions (NC) but performances remains intact (but slower) in habitual conditions (HC). Mean success rate saline muscimol HC Number of trials NC Mean success rate * * * * HC NC HC NC Saline Muscimol Mean of last 25 trials Piron et al. (submitted)

19 Experimental conclusion If habits were stored in basal ganglia, monkeys would not achieve peak performances in muscimol conditions for familiar stimuli. If habits were learned in cortex, monkeys would be able to reach peak performances in muscimol conditions for unfamiliar stimuli. 1.0 Mean success rate saline muscimol HC Number of trials NC Piron et al. (submitted)

20 Computational model Neural Network Neuron Rate model Two segregated loops: Cognitive loop allows to choose a shape Motor loop allows to reach a shape External current 2 External current Cortex + External current Cortex associative (4x4 units) Cortex GPe HYPERDIRECT PATHWAY Striatum DIRECT PATHWAY Striatum associative (4x4 units) 3 Striatum GPe INDIRECT PATHWAY STN GPi GPi STN Thalamus Thalamus Topalidou et al. (in prep.)

21 Corticobasal competition Cognitive decision has to intervene in decision. Cortical decision Thanks to lateral competition, cortex can take a decision without interaction with BG. External current External current External current Cortex 2 + Cortex associative (4x4 units) Cortex CorticoBasal decision GPe HYPERDIRECT PATHWAY Striatum DIRECT PATHWAY Striatum associative (4x4 units) 3 Striatum GPe INDIRECT PATHWAY STN GPi GPi STN Thalamus Thalamus Topalidou et al. (in prep.)

22 Acting is learning Learning occurs at three different places simultaneously. 1 & 2 Hebbian learning 3 Reinforcement learning Cortex learns to reproduce previous repertories, regardless of whether or not are appropriate (HL). Fast basal ganglia trialanderror learning (RL) biases slow cortical one (HL) ensuring that the correct behavior is produced. Hélie et al. (2014) External current 2 External current GPe INDIRECT PATHWAY Cortex HYPERDIRECT PATHWAY STN Striatum DIRECT PATHWAY + GPi Thalamus External current Cortex associative (4x4 units) Striatum associative (4x4 units) GPi Thalamus Striatum Cortex 3 STN GPe Topalidou et al. (in prep.)

23 Computational results Intact model peak performances on familiar conditions can learn novel conditions Lesioned model (GPi) peak performances on familiar conditions cannot learn novel conditions External current + External current External current (Monkey results) GPe INDIRECT PATHWAY Cortex HYPERDIRECT PATHWAY STN 2 Striatum DIRECT PATHWAY GPi Thalamus Cortex associative (4x4 units) Striatum associative (4x4 units) GPi Thalamus Striatum Cortex 3 STN GPe Mean success rate saline muscimol HC Number of trials NC Topalidou et al. (in prep.)

24 Sensitivity to reward devaluation

25 Conclusion The acquisition and the expression of habits are two entangled processes that can be dissociated experimentally. This experimental dissociation sheds light on the nature of the interaction between the basal ganglia and the cortex and their respective role in the initial formation and the later expression of habits. The model suggests that the basal ganglia implicitly supervises the cortex where habits are actually stored, but the cortex cannot learn them on its own. In the future, the model will be tested in different protocols in order to ensure the accuracy of its predictions.

26 Acknowledgements Nicolas Rougier T. Boraud C. Piron D. Kase A. Leblois

27 Acknowledgements Nicolas Rougier T. Boraud C. Piron D. Kase A. Leblois

28 Acknowledgements Nicolas Rougier T. Boraud C. Piron D. Kase A. Leblois

29 Acknowledgements Nicolas Rougier T. Boraud C. Piron D. Kase A. Leblois

30 Acknowledgements Nicolas Rougier T. Boraud C. Piron D. Kase A. Leblois

31

32 Reaction period (ms) * * * * HC NC HC NC Saline Muscimol

Instrumental Conditioning VI: There is more than one kind of learning

Instrumental Conditioning VI: There is more than one kind of learning Instrumental Conditioning VI: There is more than one kind of learning PSY/NEU338: Animal learning and decision making: Psychological, computational and neural perspectives outline what goes into instrumental

More information

GBME graduate course. Chapter 43. The Basal Ganglia

GBME graduate course. Chapter 43. The Basal Ganglia GBME graduate course Chapter 43. The Basal Ganglia Basal ganglia in history Parkinson s disease Huntington s disease Parkinson s disease 1817 Parkinson's disease (PD) is a degenerative disorder of the

More information

Category Learning in the Brain

Category Learning in the Brain Aline Richtermeier Category Learning in the Brain The key to human intelligence Based on the article by: Seger, C.A. & Miller, E.K. (2010). Annual Review of Neuroscience, 33, 203-219. Categorization Ability

More information

Teach-SHEET Basal Ganglia

Teach-SHEET Basal Ganglia Teach-SHEET Basal Ganglia Purves D, et al. Neuroscience, 5 th Ed., Sinauer Associates, 2012 Common organizational principles Basic Circuits or Loops: Motor loop concerned with learned movements (scaling

More information

THE BRAIN HABIT BRIDGING THE CONSCIOUS AND UNCONSCIOUS MIND

THE BRAIN HABIT BRIDGING THE CONSCIOUS AND UNCONSCIOUS MIND THE BRAIN HABIT BRIDGING THE CONSCIOUS AND UNCONSCIOUS MIND Mary ET Boyle, Ph. D. Department of Cognitive Science UCSD How did I get here? What did I do? Start driving home after work Aware when you left

More information

Gangli della Base: un network multifunzionale

Gangli della Base: un network multifunzionale Gangli della Base: un network multifunzionale Prof. Giovanni Abbruzzese Centro per la Malattia di Parkinson e i Disordini del Movimento DiNOGMI, Università di Genova IRCCS AOU San Martino IST Basal Ganglia

More information

Anatomy of the basal ganglia. Dana Cohen Gonda Brain Research Center, room 410

Anatomy of the basal ganglia. Dana Cohen Gonda Brain Research Center, room 410 Anatomy of the basal ganglia Dana Cohen Gonda Brain Research Center, room 410 danacoh@gmail.com The basal ganglia The nuclei form a small minority of the brain s neuronal population. Little is known about

More information

COGNITIVE SCIENCE 107A. Motor Systems: Basal Ganglia. Jaime A. Pineda, Ph.D.

COGNITIVE SCIENCE 107A. Motor Systems: Basal Ganglia. Jaime A. Pineda, Ph.D. COGNITIVE SCIENCE 107A Motor Systems: Basal Ganglia Jaime A. Pineda, Ph.D. Two major descending s Pyramidal vs. extrapyramidal Motor cortex Pyramidal system Pathway for voluntary movement Most fibers originate

More information

Computational cognitive neuroscience: 8. Motor Control and Reinforcement Learning

Computational cognitive neuroscience: 8. Motor Control and Reinforcement Learning 1 Computational cognitive neuroscience: 8. Motor Control and Reinforcement Learning Lubica Beňušková Centre for Cognitive Science, FMFI Comenius University in Bratislava 2 Sensory-motor loop The essence

More information

Making Things Happen 2: Motor Disorders

Making Things Happen 2: Motor Disorders Making Things Happen 2: Motor Disorders How Your Brain Works Prof. Jan Schnupp wschnupp@cityu.edu.hk HowYourBrainWorks.net On the Menu in This Lecture In the previous lecture we saw how motor cortex and

More information

BIOMED 509. Executive Control UNM SOM. Primate Research Inst. Kyoto,Japan. Cambridge University. JL Brigman

BIOMED 509. Executive Control UNM SOM. Primate Research Inst. Kyoto,Japan. Cambridge University. JL Brigman BIOMED 509 Executive Control Cambridge University Primate Research Inst. Kyoto,Japan UNM SOM JL Brigman 4-7-17 Symptoms and Assays of Cognitive Disorders Symptoms of Cognitive Disorders Learning & Memory

More information

This is a repository copy of Goal-directed and habitual control in the basal ganglia: implications for Parkinson's disease.

This is a repository copy of Goal-directed and habitual control in the basal ganglia: implications for Parkinson's disease. This is a repository copy of Goal-directed and habitual control in the basal ganglia: implications for Parkinson's disease. White Rose Research Online URL for this paper: http://eprints.whiterose.ac.uk/110882/

More information

Basal Ganglia. Introduction. Basal Ganglia at a Glance. Role of the BG

Basal Ganglia. Introduction. Basal Ganglia at a Glance. Role of the BG Basal Ganglia Shepherd (2004) Chapter 9 Charles J. Wilson Instructor: Yoonsuck Choe; CPSC 644 Cortical Networks Introduction A set of nuclei in the forebrain and midbrain area in mammals, birds, and reptiles.

More information

Large Scale modeling of the Basal Ganglia

Large Scale modeling of the Basal Ganglia Large Scale modeling of the Basal Ganglia Thesis submitted in partial fulfillment of the requirements for the degree of Master of Sciences by Research in Computer Science Engineering by Bhargav Teja Nallapu

More information

Cortical and basal ganglia contributions to habit learning and automaticity

Cortical and basal ganglia contributions to habit learning and automaticity Review Perceptual learning, motor learning and automaticity Cortical and basal ganglia contributions to habit learning and automaticity F. Gregory Ashby 1, Benjamin O. Turner 1 and Jon C. Horvitz 2 1 Department

More information

The Globus Pallidus Pars Interna in Goal-Oriented and Routine Behaviors: Resolving a Long-Standing Paradox

The Globus Pallidus Pars Interna in Goal-Oriented and Routine Behaviors: Resolving a Long-Standing Paradox The Globus Pallidus Pars Interna in Goal-Oriented and Routine Behaviors: Resolving a Long-Standing Paradox Camille Piron, Daisuke Kase, Meropi Topalidou, Michel Goillandeau, Hugues Orignac, Tho-Hai Nguyen,

More information

ISIS NeuroSTIC. Un modèle computationnel de l amygdale pour l apprentissage pavlovien.

ISIS NeuroSTIC. Un modèle computationnel de l amygdale pour l apprentissage pavlovien. ISIS NeuroSTIC Un modèle computationnel de l amygdale pour l apprentissage pavlovien Frederic.Alexandre@inria.fr An important (but rarely addressed) question: How can animals and humans adapt (survive)

More information

Research Article A Biologically Inspired Computational Model of Basal Ganglia in Action Selection

Research Article A Biologically Inspired Computational Model of Basal Ganglia in Action Selection Computational Intelligence and Neuroscience Volume 25, Article ID 8747, 24 pages http://dx.doi.org/.55/25/8747 Research Article A Biologically Inspired Computational Model of Basal Ganglia in Action Selection

More information

Degree of freedom problem

Degree of freedom problem KINE 4500 Neural Control of Movement Lecture #1:Introduction to the Neural Control of Movement Neural control of movement Kinesiology: study of movement Here we re looking at the control system, and what

More information

Reinforcement Learning and Dimensionality Reduction: a model in Computational Neuroscience

Reinforcement Learning and Dimensionality Reduction: a model in Computational Neuroscience Reinforcement Learning and Dimensionality Reduction: a model in Computational Neuroscience Nishal Shah, Frédéric Alexandre To cite this version: Nishal Shah, Frédéric Alexandre. Reinforcement Learning

More information

KINE 4500 Neural Control of Movement. Lecture #1:Introduction to the Neural Control of Movement. Neural control of movement

KINE 4500 Neural Control of Movement. Lecture #1:Introduction to the Neural Control of Movement. Neural control of movement KINE 4500 Neural Control of Movement Lecture #1:Introduction to the Neural Control of Movement Neural control of movement Kinesiology: study of movement Here we re looking at the control system, and what

More information

Habits, action sequences and reinforcement learning

Habits, action sequences and reinforcement learning European Journal of Neuroscience European Journal of Neuroscience, Vol. 35, pp. 1036 1051, 2012 doi:10.1111/j.1460-9568.2012.08050.x Habits, action sequences and reinforcement learning Amir Dezfouli and

More information

A Neurocomputational Model of Dopamine and Prefrontal Striatal Interactions during Multicue Category Learning by Parkinson Patients

A Neurocomputational Model of Dopamine and Prefrontal Striatal Interactions during Multicue Category Learning by Parkinson Patients A Neurocomputational Model of Dopamine and Prefrontal Striatal Interactions during Multicue Category Learning by Parkinson Patients Ahmed A. Moustafa and Mark A. Gluck Abstract Most existing models of

More information

Basal ganglia Sujata Sofat, class of 2009

Basal ganglia Sujata Sofat, class of 2009 Basal ganglia Sujata Sofat, class of 2009 Basal ganglia Objectives Describe the function of the Basal Ganglia in movement Define the BG components and their locations Describe the motor loop of the BG

More information

THE BRAIN HABIT BRIDGING THE CONSCIOUS AND UNCONSCIOUS MIND. Mary ET Boyle, Ph. D. Department of Cognitive Science UCSD

THE BRAIN HABIT BRIDGING THE CONSCIOUS AND UNCONSCIOUS MIND. Mary ET Boyle, Ph. D. Department of Cognitive Science UCSD THE BRAIN HABIT BRIDGING THE CONSCIOUS AND UNCONSCIOUS MIND Mary ET Boyle, Ph. D. Department of Cognitive Science UCSD Linking thought and movement simultaneously! Forebrain Basal ganglia Midbrain and

More information

Brain anatomy and artificial intelligence. L. Andrew Coward Australian National University, Canberra, ACT 0200, Australia

Brain anatomy and artificial intelligence. L. Andrew Coward Australian National University, Canberra, ACT 0200, Australia Brain anatomy and artificial intelligence L. Andrew Coward Australian National University, Canberra, ACT 0200, Australia The Fourth Conference on Artificial General Intelligence August 2011 Architectures

More information

This Lecture: Psychology of Memory and Brain Areas Involved

This Lecture: Psychology of Memory and Brain Areas Involved Lecture 18 (Nov 24 th ): LEARNING & MEMORY #1 Lecture Outline This Lecture: Psychology of Memory and Brain Areas Involved Next lecture: Neural Mechanisms for Memory 1) Psychology of Memory: Short Term

More information

Artificial Neural Networks (Ref: Negnevitsky, M. Artificial Intelligence, Chapter 6)

Artificial Neural Networks (Ref: Negnevitsky, M. Artificial Intelligence, Chapter 6) Artificial Neural Networks (Ref: Negnevitsky, M. Artificial Intelligence, Chapter 6) BPNN in Practice Week 3 Lecture Notes page 1 of 1 The Hopfield Network In this network, it was designed on analogy of

More information

3 A Tripartite Cognitive Architecture. 4 Broad Points

3 A Tripartite Cognitive Architecture. 4 Broad Points 1 Prefrontal-Hippocampal Interactions: Computational Perspective Randall C. O Reilly Department of Psychology Center for Neuroscience Institute of Cognitive Science University of Colorado Boulder 2 Tripartite

More information

For more information about how to cite these materials visit

For more information about how to cite these materials visit Author(s): Peter Hitchcock, PH.D., 2009 License: Unless otherwise noted, this material is made available under the terms of the Creative Commons Attribution Non-commercial Share Alike 3.0 License: http://creativecommons.org/licenses/by-nc-sa/3.0/

More information

Organization of the nervous system 2

Organization of the nervous system 2 Organization of the nervous system 2 Raghav Rajan Bio 334 Neurobiology I August 22nd 2013 1 Orienting within the brain absolute axes and relative axes SUPERIOR (above) ANTERIOR (in front) Anterior/Posterior,

More information

This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and

This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and education use, including for instruction at the authors institution

More information

Modelling Decision Making under Uncertainty Machine Learning and Neural Population Techniques. Elaine Duffin

Modelling Decision Making under Uncertainty Machine Learning and Neural Population Techniques. Elaine Duffin Modelling Decision Making under Uncertainty Machine Learning and Neural Population Techniques Elaine Duffin Submitted in accordance with the requirements for the degree of Doctor of Philosophy The University

More information

Decision neuroscience seeks neural models for how we identify, evaluate and choose

Decision neuroscience seeks neural models for how we identify, evaluate and choose VmPFC function: The value proposition Lesley K Fellows and Scott A Huettel Decision neuroscience seeks neural models for how we identify, evaluate and choose options, goals, and actions. These processes

More information

Systems Neuroscience November 29, Memory

Systems Neuroscience November 29, Memory Systems Neuroscience November 29, 2016 Memory Gabriela Michel http: www.ini.unizh.ch/~kiper/system_neurosci.html Forms of memory Different types of learning & memory rely on different brain structures

More information

Basal Ganglia Anatomy, Physiology, and Function. NS201c

Basal Ganglia Anatomy, Physiology, and Function. NS201c Basal Ganglia Anatomy, Physiology, and Function NS201c Human Basal Ganglia Anatomy Basal Ganglia Circuits: The Classical Model of Direct and Indirect Pathway Function Motor Cortex Premotor Cortex + Glutamate

More information

A Computational Model of Complex Skill Learning in Varied-Priority Training

A Computational Model of Complex Skill Learning in Varied-Priority Training A Computational Model of Complex Skill Learning in Varied-Priority Training 1 Wai-Tat Fu (wfu@illinois.edu), 1 Panying Rong, 1 Hyunkyu Lee, 1 Arthur F. Kramer, & 2 Ann M. Graybiel 1 Beckman Institute of

More information

Contributions of the striatum to learning, motivation, and performance: an associative account

Contributions of the striatum to learning, motivation, and performance: an associative account Review Contributions of the striatum to learning, motivation, and performance: an associative account Mimi Liljeholm and John P. O Doherty Division of the Humanities and Social Sciences, and Computation

More information

Reinforcement Learning, Conflict Monitoring, and Cognitive Control: An Integrative Model of Cingulate-Striatal Interactions and the ERN

Reinforcement Learning, Conflict Monitoring, and Cognitive Control: An Integrative Model of Cingulate-Striatal Interactions and the ERN 17 Reinforcement Learning, Conflict Monitoring, and Cognitive Control: An Integrative Model of Cingulate-Striatal Interactions and the ERN Jeffrey Cockburn and Michael Frank Fortune favors those who are

More information

Implications of a Dynamic Causal Modeling Analysis of fmri Data. Andrea Stocco University of Washington, Seattle

Implications of a Dynamic Causal Modeling Analysis of fmri Data. Andrea Stocco University of Washington, Seattle Implications of a Dynamic Causal Modeling Analysis of fmri Data Andrea Stocco University of Washington, Seattle Production Rules and Basal Ganglia Buffer Buffer Buffer Thalamus Striatum Matching Striatum

More information

Learning Working Memory Tasks by Reward Prediction in the Basal Ganglia

Learning Working Memory Tasks by Reward Prediction in the Basal Ganglia Learning Working Memory Tasks by Reward Prediction in the Basal Ganglia Bryan Loughry Department of Computer Science University of Colorado Boulder 345 UCB Boulder, CO, 80309 loughry@colorado.edu Michael

More information

CSE511 Brain & Memory Modeling Lect 22,24,25: Memory Systems

CSE511 Brain & Memory Modeling Lect 22,24,25: Memory Systems CSE511 Brain & Memory Modeling Lect 22,24,25: Memory Systems Compare Chap 31 of Purves et al., 5e Chap 24 of Bear et al., 3e Larry Wittie Computer Science, StonyBrook University http://www.cs.sunysb.edu/~cse511

More information

Basal Ganglia George R. Leichnetz, Ph.D.

Basal Ganglia George R. Leichnetz, Ph.D. Basal Ganglia George R. Leichnetz, Ph.D. OBJECTIVES 1. To understand the brain structures which constitute the basal ganglia, and their interconnections 2. To understand the consequences (clinical manifestations)

More information

A Role for Dopamine in Temporal Decision Making and Reward Maximization in Parkinsonism

A Role for Dopamine in Temporal Decision Making and Reward Maximization in Parkinsonism 12294 The Journal of Neuroscience, November 19, 2008 28(47):12294 12304 Behavioral/Systems/Cognitive A Role for Dopamine in Temporal Decision Making and Reward Maximization in Parkinsonism Ahmed A. Moustafa,

More information

On the nature of Rhythm, Time & Memory. Sundeep Teki Auditory Group Wellcome Trust Centre for Neuroimaging University College London

On the nature of Rhythm, Time & Memory. Sundeep Teki Auditory Group Wellcome Trust Centre for Neuroimaging University College London On the nature of Rhythm, Time & Memory Sundeep Teki Auditory Group Wellcome Trust Centre for Neuroimaging University College London Timing substrates Timing mechanisms Rhythm and Timing Unified timing

More information

Evaluating the roles of the basal ganglia and the cerebellum in time perception

Evaluating the roles of the basal ganglia and the cerebellum in time perception Sundeep Teki Evaluating the roles of the basal ganglia and the cerebellum in time perception Auditory Cognition Group Wellcome Trust Centre for Neuroimaging SENSORY CORTEX SMA/PRE-SMA HIPPOCAMPUS BASAL

More information

Reinforcement learning and the brain: the problems we face all day. Reinforcement Learning in the brain

Reinforcement learning and the brain: the problems we face all day. Reinforcement Learning in the brain Reinforcement learning and the brain: the problems we face all day Reinforcement Learning in the brain Reading: Y Niv, Reinforcement learning in the brain, 2009. Decision making at all levels Reinforcement

More information

Modeling the sensory roles of noradrenaline in action selection

Modeling the sensory roles of noradrenaline in action selection Modeling the sensory roles of noradrenaline in action selection Maxime Carrere, Frédéric Alexandre To cite this version: Maxime Carrere, Frédéric Alexandre. Modeling the sensory roles of noradrenaline

More information

A behavioral investigation of the algorithms underlying reinforcement learning in humans

A behavioral investigation of the algorithms underlying reinforcement learning in humans A behavioral investigation of the algorithms underlying reinforcement learning in humans Ana Catarina dos Santos Farinha Under supervision of Tiago Vaz Maia Instituto Superior Técnico Instituto de Medicina

More information

By Carrot or by Stick: Cognitive Reinforcement Learning in Parkinsonism

By Carrot or by Stick: Cognitive Reinforcement Learning in Parkinsonism By Carrot or by Stick: Cognitive Reinforcement Learning in Parkinsonism Michael J. Frank, 1* Lauren C. Seeberger, 2 Randall C. O Reilly 1* 1 Department of Psychology and Center for Neuroscience, University

More information

Emotion Explained. Edmund T. Rolls

Emotion Explained. Edmund T. Rolls Emotion Explained Edmund T. Rolls Professor of Experimental Psychology, University of Oxford and Fellow and Tutor in Psychology, Corpus Christi College, Oxford OXPORD UNIVERSITY PRESS Contents 1 Introduction:

More information

A. General features of the basal ganglia, one of our 3 major motor control centers:

A. General features of the basal ganglia, one of our 3 major motor control centers: Reading: Waxman pp. 141-146 are not very helpful! Computer Resources: HyperBrain, Chapter 12 Dental Neuroanatomy Suzanne S. Stensaas, Ph.D. March 1, 2012 THE BASAL GANGLIA Objectives: 1. What are the main

More information

The Neuroscience of Addiction: A mini-review

The Neuroscience of Addiction: A mini-review The Neuroscience of Addiction: A mini-review Jim Morrill, MD, PhD MGH Charlestown HealthCare Center Massachusetts General Hospital Disclosures Neither I nor my spouse/partner has a relevant financial relationship

More information

A. General features of the basal ganglia, one of our 3 major motor control centers:

A. General features of the basal ganglia, one of our 3 major motor control centers: Reading: Waxman pp. 141-146 are not very helpful! Computer Resources: HyperBrain, Chapter 12 Dental Neuroanatomy Suzanne S. Stensaas, Ph.D. April 22, 2010 THE BASAL GANGLIA Objectives: 1. What are the

More information

Behavioral Neuroscience: Fear thou not. Rony Paz

Behavioral Neuroscience: Fear thou not. Rony Paz Behavioral Neuroscience: Fear thou not Rony Paz Rony.paz@weizmann.ac.il Thoughts What is a reward? Learning is best motivated by threats to survival Threats are much better reinforcers Fear is a prime

More information

Learning Objectives.

Learning Objectives. Learning Objectives 1. Describe the Functions/Components/Deficits of the motor system (table) 2. Explain the difference between upper and lower motoneurons 3. Describe the roles of the Basal Ganglia and

More information

Brain Dynamics, Reward, & Mocap

Brain Dynamics, Reward, & Mocap Brain Dynamics, Reward, & Mocap Howard Poizner and David Peterson I. MC/BDL Developments II. Project 2.1.3 Update A. Science meets Art (With Scott Makeig & Terry Sejnowski) B. VR System Development a.

More information

This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and

This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and education use, including for instruction at the authors institution

More information

marijuana and the teen brain MARY ET BOYLE, PH. D. DEPARTMENT OF COGNITIVE SCIENCE UCSD

marijuana and the teen brain MARY ET BOYLE, PH. D. DEPARTMENT OF COGNITIVE SCIENCE UCSD marijuana and the teen brain MARY ET BOYLE, PH. D. DEPARTMENT OF COGNITIVE SCIENCE UCSD in this talk what is marijuana? the brain on marijuana is the teen brain special? current research what is marijuana?

More information

Choosing the Greater of Two Goods: Neural Currencies for Valuation and Decision Making

Choosing the Greater of Two Goods: Neural Currencies for Valuation and Decision Making Choosing the Greater of Two Goods: Neural Currencies for Valuation and Decision Making Leo P. Surgre, Gres S. Corrado and William T. Newsome Presenter: He Crane Huang 04/20/2010 Outline Studies on neural

More information

2. Which of the following is not an element of McGuire s chain of cognitive responses model? a. Attention b. Comprehension c. Yielding d.

2. Which of the following is not an element of McGuire s chain of cognitive responses model? a. Attention b. Comprehension c. Yielding d. Chapter 10: Cognitive Processing of Attitudes 1. McGuire s (1969) model of information processing can be best described as which of the following? a. Sequential b. Parallel c. Automatic 2. Which of the

More information

Hold your horses: A dynamic computational role for the subthalamic nucleus in decision making

Hold your horses: A dynamic computational role for the subthalamic nucleus in decision making Neural Networks 19 (2006) 1120 1136 www.elsevier.com/locate/neunet 2006 Special Issue Hold your horses: A dynamic computational role for the subthalamic nucleus in decision making Michael J. Frank,1 Department

More information

A computational model of integration between reinforcement learning and task monitoring in the prefrontal cortex

A computational model of integration between reinforcement learning and task monitoring in the prefrontal cortex A computational model of integration between reinforcement learning and task monitoring in the prefrontal cortex Mehdi Khamassi, Rene Quilodran, Pierre Enel, Emmanuel Procyk, and Peter F. Dominey INSERM

More information

A quick overview of LOCEN-ISTC-CNR theoretical analyses and system-level computational models of brain: from motivations to actions

A quick overview of LOCEN-ISTC-CNR theoretical analyses and system-level computational models of brain: from motivations to actions A quick overview of LOCEN-ISTC-CNR theoretical analyses and system-level computational models of brain: from motivations to actions Gianluca Baldassarre Laboratory of Computational Neuroscience, Institute

More information

Neuroscience of Consciousness II

Neuroscience of Consciousness II 1 C83MAB: Mind and Brain Neuroscience of Consciousness II Tobias Bast, School of Psychology, University of Nottingham 2 Consciousness State of consciousness - Being awake/alert/attentive/responsive Contents

More information

The Contribution of the Medial Prefrontal Cortex, Orbitofrontal Cortex, and Dorsomedial Striatum to Behavioral Flexibility

The Contribution of the Medial Prefrontal Cortex, Orbitofrontal Cortex, and Dorsomedial Striatum to Behavioral Flexibility The Contribution of the Medial Prefrontal Cortex, Orbitofrontal Cortex, and Dorsomedial Striatum to Behavioral Flexibility MICHAEL E. RAGOZZINO Department of Psychology, University of Illinois at Chicago,

More information

NSCI 324 Systems Neuroscience

NSCI 324 Systems Neuroscience NSCI 324 Systems Neuroscience Dopamine and Learning Michael Dorris Associate Professor of Physiology & Neuroscience Studies dorrism@biomed.queensu.ca http://brain.phgy.queensu.ca/dorrislab/ NSCI 324 Systems

More information

Data Analysis. Memory and Awareness in Fear Conditioning. Delay vs. Trace Conditioning. Discrimination and Reversal. Complex Discriminations

Data Analysis. Memory and Awareness in Fear Conditioning. Delay vs. Trace Conditioning. Discrimination and Reversal. Complex Discriminations What is Fear Conditioning? Memory and Awareness in Fear Conditioning Information and prediction: Animals use environmental signals to predict the occurrence of biologically significant events. Similar

More information

The Basal Ganglia Do Not Select Reach Targets but Control the Urgency of Commitment

The Basal Ganglia Do Not Select Reach Targets but Control the Urgency of Commitment Article The Basal Ganglia Do Not Select Reach Targets but Control the Urgency of Commitment Highlights d The BG do not contribute to deciding which movement target choice is selected d d BG activity reflects

More information

Multitasking. Multitasking. Intro Problem Solving in Computer Science McQuain

Multitasking. Multitasking. Intro Problem Solving in Computer Science McQuain 1 Forms of 2 There are (at least) two modes of behavior that are commonly called multitasking: - working on two or more different tasks, giving one's partial attention to each simultaneously - working

More information

Exploring Reflections and Conversations of Breaking Unconscious Racial Bias. Sydney Spears Ph.D., LSCSW

Exploring Reflections and Conversations of Breaking Unconscious Racial Bias. Sydney Spears Ph.D., LSCSW Exploring Reflections and Conversations of Breaking Unconscious Racial Bias Sydney Spears Ph.D., LSCSW Race the Power of an Illusion: The Difference Between Us https://www.youtube.com/watch?v=b7_yhur3g9g

More information

Huntington s Disease COGS 172

Huntington s Disease COGS 172 Huntington s Disease COGS 172 Overview Part I: What is HD? - Clinical description and features - Genetic basis and neuropathology - Cell biology, mouse models and therapeutics Part II: HD as a model in

More information

Online Journal Club-Article Review

Online Journal Club-Article Review Online Journal Club-Article Review Article Citation Study Objective/Purpose (hypothesis) Brief Background (why issue is important; summary of previous literature) Study Design (type of trial, randomization,

More information

The basal ganglia optimize decision making over general perceptual hypotheses

The basal ganglia optimize decision making over general perceptual hypotheses The basal ganglia optimize decision making over general perceptual hypotheses 1 Nathan F. Lepora 1 Kevin N. Gurney 1 1 Department of Psychology, University of Sheffield, Sheffield S10 2TP, U.K. Keywords:

More information

Behavioral Neuroscience: Fear thou not. Rony Paz

Behavioral Neuroscience: Fear thou not. Rony Paz Behavioral Neuroscience: Fear thou not Rony Paz Rony.paz@weizmann.ac.il Thoughts What is a reward? Learning is best motivated by threats to survival? Threats are much better reinforcers? Fear is a prime

More information

Psych3BN3 Topic 4 Emotion. Bilateral amygdala pathology: Case of S.M. (fig 9.1) S.M. s ratings of emotional intensity of faces (fig 9.

Psych3BN3 Topic 4 Emotion. Bilateral amygdala pathology: Case of S.M. (fig 9.1) S.M. s ratings of emotional intensity of faces (fig 9. Psych3BN3 Topic 4 Emotion Readings: Gazzaniga Chapter 9 Bilateral amygdala pathology: Case of S.M. (fig 9.1) SM began experiencing seizures at age 20 CT, MRI revealed amygdala atrophy, result of genetic

More information

Modeling the interplay of short-term memory and the basal ganglia in sequence processing

Modeling the interplay of short-term memory and the basal ganglia in sequence processing Neurocomputing 26}27 (1999) 687}692 Modeling the interplay of short-term memory and the basal ganglia in sequence processing Tomoki Fukai* Department of Electronics, Tokai University, Hiratsuka, Kanagawa

More information

NEURAL CONTROL OF MOVEMENT: ENGINEERING THE RHYTHMS OF THE BRAIN

NEURAL CONTROL OF MOVEMENT: ENGINEERING THE RHYTHMS OF THE BRAIN NEURAL CONTROL OF MOVEMENT: ENGINEERING THE RHYTHMS OF THE BRAIN Madeleine Lowery School of Electrical and Electronic Engineering Centre for Biomedical Engineering University College Dublin Parkinson s

More information

The Motor Systems. What s the motor system? Plan

The Motor Systems. What s the motor system? Plan The Motor Systems What s the motor system? Parts of CNS and PNS specialized for control of limb, trunk, and eye movements Also holds us together From simple reflexes (knee jerk) to voluntary movements

More information

The human brain. of cognition need to make sense gives the structure of the brain (duh). ! What is the basic physiology of this organ?

The human brain. of cognition need to make sense gives the structure of the brain (duh). ! What is the basic physiology of this organ? The human brain The human brain! What is the basic physiology of this organ?! Understanding the parts of this organ provides a hypothesis space for its function perhaps different parts perform different

More information

Cognitive Neuroscience History of Neural Networks in Artificial Intelligence The concept of neural network in artificial intelligence

Cognitive Neuroscience History of Neural Networks in Artificial Intelligence The concept of neural network in artificial intelligence Cognitive Neuroscience History of Neural Networks in Artificial Intelligence The concept of neural network in artificial intelligence To understand the network paradigm also requires examining the history

More information

Attention: Neural Mechanisms and Attentional Control Networks Attention 2

Attention: Neural Mechanisms and Attentional Control Networks Attention 2 Attention: Neural Mechanisms and Attentional Control Networks Attention 2 Hillyard(1973) Dichotic Listening Task N1 component enhanced for attended stimuli Supports early selection Effects of Voluntary

More information

Effects of lesions of the nucleus accumbens core and shell on response-specific Pavlovian i n s t ru mental transfer

Effects of lesions of the nucleus accumbens core and shell on response-specific Pavlovian i n s t ru mental transfer Effects of lesions of the nucleus accumbens core and shell on response-specific Pavlovian i n s t ru mental transfer RN Cardinal, JA Parkinson *, TW Robbins, A Dickinson, BJ Everitt Departments of Experimental

More information

Chapter 5: How Do We Learn?

Chapter 5: How Do We Learn? Chapter 5: How Do We Learn? Defining Learning A relatively permanent change in behavior or the potential for behavior that results from experience Results from many life experiences, not just structured

More information

A Dual Process Reinforcement Learning Account for Sequential Decision Making and Skill Learning

A Dual Process Reinforcement Learning Account for Sequential Decision Making and Skill Learning A Dual Process Reinforcement Learning Account for Sequential Decision Making and Skill Learning Thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer

More information

THE AMYGDALA AND REWARD

THE AMYGDALA AND REWARD THE AMYGDALA AND REWARD Mark G. Baxter* and Elisabeth A. Murray The amygdala an almond-shaped group of nuclei at the heart of the telencephalon has been associated with a range of cognitive functions,

More information

Hold Your Horses: A Dynamic Computational Role for the Subthalamic Nucleus in Decision Making

Hold Your Horses: A Dynamic Computational Role for the Subthalamic Nucleus in Decision Making Frank 1 Hold Your Horses: A Dynamic Computational Role for the Subthalamic Nucleus in Decision Making Michael J. Frank Dept of Psychology and Program in Neuroscience University of Arizona 1503 E University

More information

Ch 8. Learning and Memory

Ch 8. Learning and Memory Ch 8. Learning and Memory Cognitive Neuroscience: The Biology of the Mind, 2 nd Ed., M. S. Gazzaniga, R. B. Ivry, and G. R. Mangun, Norton, 2002. Summarized by H.-S. Seok, K. Kim, and B.-T. Zhang Biointelligence

More information

Two-Point Threshold Experiment

Two-Point Threshold Experiment Two-Point Threshold Experiment Neuroscience Class Activity Handout An informative experiment adapted by Don Hood, Dave Krantz, Jen Blanck, and Elizabeth Cottrell This activity provides a review of the

More information

Cost-Sensitive Learning for Biological Motion

Cost-Sensitive Learning for Biological Motion Olivier Sigaud Université Pierre et Marie Curie, PARIS 6 http://people.isir.upmc.fr/sigaud October 5, 2010 1 / 42 Table of contents The problem of movement time Statement of problem A discounted reward

More information

THE PREFRONTAL CORTEX. Connections. Dorsolateral FrontalCortex (DFPC) Inputs

THE PREFRONTAL CORTEX. Connections. Dorsolateral FrontalCortex (DFPC) Inputs THE PREFRONTAL CORTEX Connections Dorsolateral FrontalCortex (DFPC) Inputs The DPFC receives inputs predominantly from somatosensory, visual and auditory cortical association areas in the parietal, occipital

More information

Hebbian Plasticity for Improving Perceptual Decisions

Hebbian Plasticity for Improving Perceptual Decisions Hebbian Plasticity for Improving Perceptual Decisions Tsung-Ren Huang Department of Psychology, National Taiwan University trhuang@ntu.edu.tw Abstract Shibata et al. reported that humans could learn to

More information

Jonas Rose bird brains

Jonas Rose bird brains Jonas Rose bird brains Bird brains BIRDS? Who are they What tricks can they do What do their brains look like What don t we know yet What are the implications Bird evolution Birds are dinosaurs Henry Huxley

More information

How do individuals with congenital blindness form a conscious representation of a world they have never seen? brain. deprived of sight?

How do individuals with congenital blindness form a conscious representation of a world they have never seen? brain. deprived of sight? How do individuals with congenital blindness form a conscious representation of a world they have never seen? What happens to visual-devoted brain structure in individuals who are born deprived of sight?

More information

Neurophysiology of systems

Neurophysiology of systems Neurophysiology of systems Motor cortex (voluntary movements) Dana Cohen, Room 410, tel: 7138 danacoh@gmail.com Voluntary movements vs. reflexes Same stimulus yields a different movement depending on context

More information

Learning. Learning: Problems. Chapter 6: Learning

Learning. Learning: Problems. Chapter 6: Learning Chapter 6: Learning 1 Learning 1. In perception we studied that we are responsive to stimuli in the external world. Although some of these stimulus-response associations are innate many are learnt. 2.

More information

Objectives. Objectives Continued 8/13/2014. Movement Education and Motor Learning Where Ortho and Neuro Rehab Collide

Objectives. Objectives Continued 8/13/2014. Movement Education and Motor Learning Where Ortho and Neuro Rehab Collide Movement Education and Motor Learning Where Ortho and Neuro Rehab Collide Roderick Henderson, PT, ScD, OCS Wendy Herbert, PT, PhD Janna McGaugh, PT, ScD, COMT Jill Seale, PT, PhD, NCS Objectives 1. Identify

More information

The Nature of the Potential

The Nature of the Potential Lawrence May 2017 The Nature of the Potential Bita Moghaddam Professor and Chair Department of Behavioral Neuroscience Oregon Health and Science University Research Support: NIH/NIMH Andrew Mellon Foundation

More information

Basal Ganglia. Steven McLoon Department of Neuroscience University of Minnesota

Basal Ganglia. Steven McLoon Department of Neuroscience University of Minnesota Basal Ganglia Steven McLoon Department of Neuroscience University of Minnesota 1 Course News Graduate School Discussion Wednesday, Nov 1, 11:00am MoosT 2-690 with Paul Mermelstein (invite your friends)

More information

Distinct valuation subsystems in the human brain for effort and delay

Distinct valuation subsystems in the human brain for effort and delay Supplemental material for Distinct valuation subsystems in the human brain for effort and delay Charlotte Prévost, Mathias Pessiglione, Elise Météreau, Marie-Laure Cléry-Melin and Jean-Claude Dreher This

More information